Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/264406 
Year of Publication: 
2019
Citation: 
[Journal:] The Journal of Entrepreneurial Finance (JEF) [ISSN:] 1551-9570 [Volume:] 21 [Issue:] 2 [Publisher:] The Academy of Entrepreneurial Finance (AEF) [Place:] Los Angeles, CA [Year:] 2019 [Pages:] 1-25
Publisher: 
The Academy of Entrepreneurial Finance (AEF), Los Angeles, CA
Abstract: 
The decision of a venture capitalist to commit capital in a new risky business is a complex decision. Investors need to consider a number of important criteria simultaneously. Based on the postulates of signaling theory and the investment criteria outlined in the extant literature, we propose a theoretical framework to describe the relationship between a new venture's characteristics and the funding decision. The proposed framework is tested using actual data of a unique sample of 200 new Egyptian technological startups. The startups were tracked from establishment until applying to a venture capitalist and a decision was made either to accept or to reject them. Logistic regression analysis reveals that venture capitalists prefer to invest in startups with mature products and an initial proof of financial performance. The entrepreneurs' industry experience and the size of their social networks are important factors that affect the startup's access to finance. Using decision tree analysis to map venture capitalists' decisions, we show that the time of applying for funds is critical and serves as a gateway for further evaluation. Startups are more likely rejected for applying later into the VC fund than for lack of experience or unproved products. This suggests that the development of the Egyptian tech ecosystem may be hugely constrained by the limited availability of capital as well as the high aversion to risk on the behalf of venture capitalists.
Subjects: 
venture capital
selection criteria
emerging
tech startups
entrepreneurial finance
Egypt
Decision trees
JEL: 
G24
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

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